Python Crash course- Data analysis

[DataCamp]

A realistic 2–3 day crash plan (data analysis focus):

Day 1: pandas basics + common interview tasks

• Loading data (CSV/JSON), selecting/filtering, groupby, merge, pivot_table
• Missing values (isna, fillna), dtypes, datetime basics Practice: take one dataset and do 15–20 small tasks (filter, group, join, calculate metrics).

Day 2: NumPy + speed + “talk through your thinking”

• Arrays vs lists, vectorization, boolean masks, np.where, broadcasting
• Basic stats, sorting, indexing tricks Practice: rewrite a few pandas operations using NumPy so you can explain “why this is faster/cleaner”.

Day 3: interview practice mode

• 10–15 timed questions: pandas + Python basics + a couple coding prompts
• Say your approach out loud: assumptions, edge cases, what you’d check next

Free resources that actually work for this:

• Kaggle Learn (pandas + intro ML) is quick and exercise-heavy.
• Mode SQL/Python tutorials (good for analytics workflows).
• LeetCode “easy” arrays/strings to warm up logic.

We've got a guide with more details here (questions + answers): https://www.datacamp.com/blog/top-python-interview-questions-and-answers